Summary of Inside the Black Box

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Inside the Black Box book summary
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Rating

8

Qualities

  • Innovative
  • Applicable

Recommendation

Hedge fund manager Rishi K. Narang set out to climb Mount Everest by trying to shed light on an area of the investment world – quantitative strategies and high-frequency trading – that many call a “black box.” The summit that Narang reaches is in the achievement of explaining to the layperson and breaking down a complex and oft-misunderstood subject in an entertaining way. His book – a lively mixture of plain English, helpful analogies and real-life examples – provides a thorough walk-through showing how a quantitative strategy fund actually operates. Narang debunks many of the myths that surround quantitative trading and opens that black box to the light of day. getAbstract recommends his useful guide to anyone who wants to invest in or simply understand “quant” funds. Fear of technology and change has discouraged many investors from this sector, but, as time goes on, quantitative trading will likely become mainstream. Narang’s treatise will ensure you don’t get left behind.

About the Author

Rishi K. Narang founded and runs Telesis Capital LLC, a quantitative-strategy investment management company. He has worked in the hedge fund industry since 1996.

 

Summary

In Search of Alpha

Quantitative trading strategies employ computer technology and mathematical models to identify and take advantage of trading opportunities in the pursuit of alpha, which is “returns that are independent of the direction of any market in the long run.” To achieve alpha, traders of quantitative strategies – called “quants” – must find ways to achieve net returns over and above what investors would have received if they had simply bought an index of stocks.

Traditional investment managers typically use personal discretion to make these decisions. What separates quants from those “discretionary traders” is how quants invent and execute their strategies, not necessarily the strategies themselves. Quants use computers and algorithms; discretionary traders make “decisions driven by emotion, indiscipline, passion, greed and fear.”

Investors, managers and traders who rely on discretion to implement strategies are prone to using mental shortcuts or behavioral biases, such as holding on to falling stocks. In quantitative trading, computers dispassionately execute commands based on vital, front-end human input – in the form of thorough research, software...


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    a. A. 7 years ago
    Considering the recent 60 Minutes report, I'd consider this abstract a must read for anyone invested in the stock market!!